{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\Anaconda\\lib\\site-packages\\jqdatasdk\\api.py:34: PanelObsoleteWarning: 当前环境 pandas 版本高于 0.25，get_price 与 get_fundamentals_continuously 接口的 panel 参数将固定为 False（0.25 及以上版本的 pandas 不再支持 panel，如使用该数据结构和相关函数请注意修改）\n",
      "  warnings.warn(PandasChecker.VERSION_NOTICE_MESSAGE, PanelObsoleteWarning)\n"
     ]
    },
    {
     "data": {
      "image/png": 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hL3Pgv99V5WlbalTMuC86u1COuCZYy3Yo19XqP7nqtnvV2Hn7Vnjpa1B7WNVlmf9tFeHSGqFJZJohjV8CLoSwosT7JSnlf1yLy4QQ2a73s4GjvraVUj4hpZwnpZyXkZHRr8EmelngO4rraGpTwt3SHgECDsrN4e2aMIRn9//gs4c86/Uk4FIq3/k7PwBh6ljd77SfKovRae95UvPt2+CRKZ4+o5e/rEL+nj5d7XPOtSql/apXlcviqdPhaDdlDBpKAQlp43s9/X5hMoGjTT23xqhU+9WPqInK0Ut8b2MI+JZX4NVr4YMfqdfSCf++RlnYp//C4/YRZhV6eM5DcG8B3LjSy/W1LWSnpgkR7S2eO7aqg8p1NsSyof2JQhHA08AuKeXDXm+9DXzT9fybQMiLfSRGW6lzCfjrG4rcyxtbI0TAM6dCWwMc2aBeZ89U2YabX4ZNL8Gsq9XyBp/XQkXFXo+fNnUMRMV63kvKgbN/p55XHfC9ffUh2PhP9fzUn8Dl/4K8hbDoVrXslP9TURyg6rhc/566IDx9lm/XTL3rbiIhu+dzDwZTLlKW/U2r4J59yrd++b+6DxG0RkPqWPV5l+1QF5njvgfJI+HoDpj/HVXt8LxHIH2i2ucPdsCC76jjxCR7XDNHNvo+hmbw8ulv4S+zVJTWk6fAJ7+B7W+Ee1RBxZ848BOAa4BtQojNrmX/B/weeFUIcQNwCPh6SEboheEDb7M7eWvzEc6YksmKnWU0R4oFbjSkKN6kHuMzlf92xU/U6znXqi9YY7kS4PfugfP/3LGM7qHVPR8j3WUJV+6FzCld39/7gXq8baPyyxuc9lOYcoFy63iTPRO+vQJevFRFaty5E+LSPe8bF5OErJ7HFQwufVZdTExm9eePb/2WdSoO31vkJ5+v3Ccn/VC9HnMS3LrO9/YJmZCUB0Vf9Xv4mgHG+J3973bImKwilba/oe4uhwj+RKGsllIKKeUMKeUs1997UspKKeVpUsrxUsrTpZR+FKzoH0kxVtodkne3FVPd1M6VC/IwmwSNrb2kWQ8WjB6ZxRuVqyIuHSafp5bZEiFnruqrWV8Cb3xbTSjuclXl+/If8Nx5sOw+1ZQZYNwZXY+R5qqfbcRGdyb/fWWVeos3KIHLmeu7qUJynrJSHa2eHwWoW9LXXDdhAyHgJpOnZoq/mC1dLfSRxyv3kL/ZoSPmeu6aAuHt2ztGGWkGFmPeYs61ygiZ8XUVZVWyZciUWIiYVHpQAg7wzOoCMhJsLB6fTmyU2e0LH/QkutwMVQdUB3uTWblBRiyACWcpsYnLgB1vKsGwxCiLu6kKlv0Q6orVpNo1/4VbN8AZv+x6jKg45SLwVYa1rUmFxE04K/CxG772Mld1v+pD6pbUoD+JOoOdnHkqJLI+gGintkbY+LyaqwhWkpXGf4zG2QtuVK37bAkw/gwVhfSPJR7DI8KJSAHfdqSWS2bnYDGbiI0y0xwpAm5LhChXpIZ3zPI334YL/6aex2WoL9nMK2HqxXDoC09P0NN+qjIMR8xVvtvurNEZX4d9H0HN4Y7LD65SE3fjzwx87DHJypVglGdd90TH900R9VUKjBHz1eORAGqMl3jVvTFqmwebxgp1V/blEzpbtDMNR6GtvuPkuvF/BP/LFA9yIupXlxjjcdl/ba7yC8dFWWhsixAXihCeyT7vST9rjEeMs2aoqnpLH4Dc+SoErvBL9Z4xudgbc65Vjxue77h87/vqAjLyhL6NP3OqSplf/n+w+V8qbPFYIHsGmCyB+cG9a8LkLw/ueKoLlHttzzJ1R7XsHnjqNE+Wr0bNAUFHV6HZ6olYMiKUIpyIEvBhCdEAnD45kwmZCQDERJIFDp7+kN1Zwaf+CL63FqITPdZDgWvi0t9Ij+Q8tf9NL6g0+XVPKks+/33VHShQP7LBzG8oS3zDcyoFfdEtKkpj5hV921+kYI2BzF66/BRvUglABgWfqzmPGZeru6FgWsivf0tNKH/xqCpf8LWnVZjc8vuDd4y+ULodPnt4cLiMKvepx/RO4a1XvQ4n3acCBYZAu76IqUYIMDErgTdvOYHpOUnuZbFR5sixwEH54poqYdrXul/HmHQzrIeCzwAR2EThvOtVh5rN/4L37vYsP7kfJWumXqz+pFQXBksU3Php3/cXSYyYp+LJu6tsuOxeJWB37VbiseddWHyXin7Y+oq6ixp5fHDGYrjGKvaoi+f0S5VFbpRBGGgajqpEsE0vAlJlCZ/zYHjGYlCxV1Wk9E7SAhXzb9SLr9wPOXO6bhtBRJQFDjArNxmzyRMpERtliSwL/Or/wJWv+RcBkZCt0u+bKpVv3Gz1/zjjz1Rf3s4daSYsDWy8vhCi71Z8pDJivorh9+WmaKlT1nl7I2z9N3zwE5XGf8IdMOkciE5SjZor9/e/GmVrvfJ9TzwXFt8NJ96plqePh/ri8GSMvnadurgtugWmf10V/wq3FV65T0Vb+ZqbMSK1vJPT2hph4wsdawL9YbwqMDeIiTgB74yywCNIwNPGwgQ/JxGFUF9C8ESw+IvJrBJSDBKGwyVPqTBFTeDkzFOPnf3g9lZVM0Y6VHjnR79SkUMn36fcYFFxKmEofzk8Ogd+O7x/lnLpNkDC3G/CaT+BjAlqefpE9dhd+Gig1BbBttfhw1+ocNE3vg1r/qaim7wrNlbsUxm9p/5IdVCadI76LMp3B2ccfaVyn5ro90X6BFUmYf3TnnNZ+aAqo7D13+r1u3dC41E4+KmaKP73NVC8eQAGHhgR5ULxRcRZ4IGSMUGVeDViyAPhhO+raBdrLEy9KOhDO6ZIG6s6/RzZoMTTYMebKsokLkOJ9rt3qbkL78Jep/5YhbBV7FUiUfSVSh7qC/s+VDkEOXM7Lk93CXl5ftf3AsHpUM0zPv6Nivv3Zttr6vG8R2DWVbDip0rQhUn5+kHNFYAKNx0+q+/j6IyjXbmOmquVO6sn7G1qonfKhb7fN5nVb+OdH6holBHzYIerQsjKB5RQGz70t29Xd15RCbDrbZWdfOavYdjkYJ1ZvxgCAh5hPvBAOeOXKjuyu3ofPSGEKiil6T9CKKutvlNhr70fKHfJXfkqRHP3e0ocvN1dQqjyunnHqdZwRlhoZwxr0FcyFahmFpteUu4x72xYUNUazVGeOP2+ULFP3U0UrVNFvk6+T7lCnj6943of/lyFxH75uHq94EbPHWLqGJW/UPil+mxGngBzvqnKGnSHw5Vd6+u8nU5VKfOjX3gmHa9f1nU+QUqVoJMySt0ROO0dwwY7M/NK+PQBWPUHNQFcV6QufA3las7CEqNKIbc1wMRz4OJ/KNfQ53+Gt26F73zU0yc5YES+gNsiKJGnLySNgONvDfcoNKAicLwz+JwOZRFPPEf5WqNi4Zr/dLe1IjEHNr+kXC8XPubx0RZ+Bf+8QNWnWfQ939vuW6GKhxlhot6YrepC7yuByxcOu6fEgNMJ6/6h3CUWG1zyJEy/TL3vsKs7uPYmuOoNdUf35KnKMgVVA/5kr+gXk1mVcDDq7ex8S4ne+X9WdyG+ePVaFcVz7h+VZRudpC5ysamqWUfhWhi1GCadq6z+D37SVUAPfKJqvSNUqGxCtu9MZQNrtPpdffBj9XreDaqOkFHYDOBXw9RdyNRLlDts8Z3KV776EVVb3rv6ZpiIfB+41UKb3YndEWAnGo0mUKKT1S28QdF6Vc62O2HyRdIIVVVxy788dclBNZVob1Ii3ZnaI8r63PhPVT+nuxDUkYtUTfm2Hhp/S6n287scWH6fygp+7lz1fPQSFcI64+sea9hsUZZs2ngYf7qKiT/xDjVhmz1LuROi4joeY5yXxX71Gyoa5H1XJcjOLfGkVBE79cXwyhWq+NSDo+Efi1XGZOGXKsntm/+D474Lp/1MJVR514UHFcJptqm7hryFKunN3It9Ovd69T+1Jam2fd7iDepcoeP/d+Qi5eMfJLVxIt4Cj7OpkK6mdgeJ5oi/HmkGMzEpHbvc7/1AlaAde4r/+/Cey9j8L+UKaG/2NLz2vkCAcsm8coUSmtZ6OOH27qOR8o5X1mHBahWf33nCur1FhZRuekG9XveEcsmYzEokZ13p241xwV86RpUsvkude3ddlqZdqnzJoMR89lWuMMOX4K3vwS1feSZfG13NNk75sZoXOLpLnefG59WEbOY0tb3B5PNVWeDP/wTH365cNkLAwZXKRRVImKwtHi5+XLm+fLl4Lv+XusDFJHuWjVigfP6H1wb2fw8RES/gGQnqqllY1cTU4UndrnfjP9czY0QSt54a4rrVmqFLTLIS2MNrVRJN1QHVUMPoYOQP3taqkWFbvEn5bOOzoKZTz8/Da9SjceGYfU33+zYmL/91mcocXXgzLLlHjfv58z3p40vuUbVr3r9fWdLfd/mOu6Pze9YYVdK3OzImqGMY8zZGk+u3blGP79+vsnqrC1SdH1ATnrkL1B+ouYaKfM9r91hGKpfVhufUX8ZkmH+D8v2f/ovux9QdE3sIq40f1rVNX3SiuqgYHbWcTtj/kbqQHPpc/X+6m8MIAREv4AtGq3jqNfsruxVwp1OyMr+8Q/y4RhMwMSlKaN++zROud9rPAtuHIeBxGSqqQkqVtQkquWvtY+oCkTNPuQBKt6nyCtZYtW3nKpLexKWpksW1hWqsax5T8dnzrlfibYmGy55TomWExFljexbvvnLqjz3Pc+aoCVajIce+D9V4bImedndGbLbBqBNVNMyITgIOyjKuyIf9n6iLwXt3Kx/5ghuDfx6+GHm8ckMVb1IJXMaFGNT/zVcZ5xAR8T6H7KQYRqfHsWa/CrhfvbeCC/+6ukOXntK6FlrtTtrs2k+u6QfRyerR5OXCCMT/DWrS79yHVRKOvUVZ8V8+rqxVI+zumbPgT9Ph41+rybms6XDtm0q4esNIEFtyj8qSTR+vIi1MVrhzl8fizJqurMXrQlRoyxtrjIpEAZV4dPsm+L8SuHuvZ53kvI7bjDtDhStOvbjr/oSAjIlw3M1q0nfyBaonrHdzk1CSt0jNVzxxsidhyKC6wPO8oVwVNfvzTOU+CgERb4EDzB2Zwqp81Ybsrc1H2FJUy86SOubkqVvbgspGANr0RKemPxi+0ApXNmZSnifu2V+sMeqWP/999XrZvcoKPe3nHeOus6Yp4QV1DH97iyaPVP703AXqgnD9MhUJ4rR3zP41meHCvwY29v5wxi+V+2HhzR3dEjesgKM7u5YnMFu673XqzeI7gztOfxh7Cow9Tf2PTrhDzSms+Kl6z4gfB+W2Kndle25/o6MvP0gMCQHPTLRR1diG0yn5qkD51HYUewl4hZqVb9UWuKY/GL5up11Zhmf8su/+TsPi3LdCTcyNmKsiTTImqYiIcaepxJ+vnlK1TvzlvD+pbbNnqddCDI4krqhYFRnSGW+/d6QQndQxXHTc6bDiZ4D0CLiUHvEGVUzO3to10qWfRLwLBSA1zobdKdlf3kBBpRLrncW1NLc5kFJyyLDAtYBr+oPhQgEV5dH5tj8QjG2FSbkBQAnDLV8qAQbl/lj6QNeJtJ6IS1NZoAM4kXbMkzlVuadyF6p6N9C1Cbi9uaOvPEgMCQs8LU4VVlq+vRSA1Lgo1uyvZPJPl3P/0kkcrNACrgkC3uFk/Z34i4pTE3ejlyh/riayScxWsfL5y1SC12pX//er31B1iHa/o9xbQWZoCHi8S8B3lBJjNXPVwjwe/VjdyqzYWUZ9i0oe0D5wTb/wbgIwanH/93fzahWdoRkajF4Cm19UmaW731GROEZSU4giU4aIC0X9CHYU1zE7L5nzZ3o614xKj+NQlbbANUEgKg6+uwbuO+x/Q+SesMb4ri2uiUzGn6FcYrvfUeUOFt/d+zb9ZGhY4HGeiYH5o1KZkJnA9Jwkth2pZd/RBlranZiEFnBNEBjAGF9NhBGbqmrIONpUqOgAzEMMCQE3LHDwJPa8dvMirnxyLduP1AEwKi2OmuZ+FtPXaDSanrjkid7XCSJDwoUSZTGREG3BYhLMzksGINpqJj3e5vZ7T8hMoNUruUej0WginSEh4ADp8Tam5iQRG+W5qUiOVRlzUWYTI9Nj9SSmRqMZUgwJFwrA/50zmcTojqeTEqtcK7mpMURbzLQ7JE6nxKRromg0miFArxa4EOIZIcRRIcR2r2WzhBBrhRCbhRDrhRBhT6U6Y0omC8ekdViW7BLw0elxRFnUqWorXKPRDBX8caE8B5zdadmDwC+klLOAn7peDzoMF8rItDhsWsA1Gs0Qo1cBl1KuAqo6LwYSXc+TgOIgjysopLgEfJS3Ba5DCTUazRChrz7wO4D3hRAPoS4Cx3e3ohDiRuBGgLy8ftSO6AMjUlR5yclZCewvbwC0gGs0mqFDX6NQvgv8QEqZC/wAeLq7FaWUT0gp50kp52VkZHS3WkiYlpPEx3edxLxRqdoC12g0Q46+Cvg3AaOe4mtA2Ccxu2NMhuocHWVWKcvaB67RaIYKfRXwYuAk1/NTgb09rDsoMCzw1nYt4BqNZmjQqw9cCPEycDKQLoQoAn4GfAf4sxDCArTg8nEPZjxhhDobU6PRDA16FXAp5RXdvDU3yGMJKVFmlwU+QD7wh1fks3h8OvNHBaFqnUaj0fhgyKTS98ZATmIWVTfxl4/2ctnja0J+LI1Gc+xyzAi4rRsBf3HtIU556FMcThm0Y322t8L9vLqxLWj71QxevthfwesbisI9DM0xxjEn4PvKG5DSI9Y/fnM7BysaaWyzB+1Yq/LL3c8/zT8atP1qBi83/XMDd7+2hd2ldeEeiuYY4pgRcMOF8uDyPVz11Jc4nZKjdS3u95tagzO5aXc4Wb2vgkvnjiAx2sK6g52TWDVDkRGpKmnsLx8N+oAszRBiyFQj7A1DwAG+2F/JwcpG/v7pfveyhtb+W+A1TW3sL2+kvsXOyRMzqGlq48sDWsCPBSyuCpcf7jpKXUs7idHWMI9Icyxw7Fjg5o6n+uhHe3l9QxGTshIAaOqnC6WgopFZv1zBrf/aiEnAieNUBMqBikYqG1r7tW/N4Keh1U5uagxtdiePfbyvg5tOowkVx4yAx9nUzcbl83OJjTLz5uZixg2L576lkwBo7KcLZVeJ8n2W1LYwY0QyybFR7losFQ16InOoU99i58Rx6XxjXi7/WHWAX72zS4u4JuQcMy6UaKuZDT8+nZTYKA5UNLK+oIo/XDoDk6vxaGM/XSgHKhrdz5eMTwcgwdVgoqFV9+Ic6jS22om3Wbh/6WRibWae+fwgTin5+QVTwz00zRDmmBFwgLR41b3+nrMmUlLbwuy8FPYdVVUK+xuFkl9W735+0kRVtCveJeD1LcGLcNEMPuwOJ83tDuJsFkwmwU/Pm4LdIXl+TQFXLMhjostNp9EEm2PGheLN/FGpXDBzOABxNlXkqqmtfy6UvWUNLBydyt+vmsOcvBQAEmyGBa4FfCjT6PruxLv+30II7jxjAnFRFv7+6b5wDk0zxDkmBdwbowlyf10oh6uamJydyNLp2QiXW0Zb4McGxgXaEHCAlLgoLp6dw7LtpdQ2axeaJjQc8wIeF6Us8P5MYkopaWyzd2mqbPygG7SAD1kKq5o48YGPAc8F2+CyeSNotTv5YEdpOIamOQY45gXcYjZhs5j6FUbYanciJUS7LgYGcVEWhIAVO8tYX6DjwYciXxVUYQSbxNk6Cvi04UnERpnZUayzMzWh4ZgXcFA/vP5MYra0K+s9xtpRwE0mQXyUhXUFVfx+2e5+jVEzODlc1eR+ntBJwE0mwfjMBPYere+8mUYTFLSAA7FR5n65UIwJ0M4CDp7b6qLq5j7vXzN4OVzpEfDOLhSACcPi2VPaMJBD0hxDaAFH+ar7M4nZbFjgUV0FXLgey+pbdD/OIYi3BR4X1VXAJ2YlUNHQSpWuSqkJAVrAURZ4f8IIm3uwwOtdFwYpoaRWW+FDDW8Bj7d1FfCxrp6sB70SvTSaYHFMJfJ0R5zN0q9Qv54scO/9FlU3MzItrs/H0QwumtscHK1vZUp2Ik4pSYzpWsAqI0Elj+l6OJpQoC1wIDHaSk1TYLe4976+lf9tKQY8FnisDwH35oj2gw8pCquV9X3TSWNYfscSzCbRZZ20+ChA18PRhAYt4EBuaixF1c3YHf75qFvaHby6oZBnPj8IeCzwaB8uFAOTUK3WNEMHYwKzp7uq1Dgl4NoC14QCLeDA6PRY7E5JcU1L7yujXCFSwubCGiobWrsNIwT4yxWzOX/mcLISo3UkyhDjkMv/nedq5uALm8VMQrSFSj2JqQkBWsCBUS4L6mClfxNNh6vUelLCyvxyTxihDxfKBTOH8+gVsxmREktRjRbwoURhVRPxNgspsT03b8iIt1GhLXBNCNACDoxOVwJe4GekwCHXrXO8zcJHu496fODW7ueER6TEaB/4EONwVRN5qbHu2jfdkRYfpQVcExK0gKMiBeKizH6Heh2uaiI2yszSaVmsyi93R5pER3X/ceakxFBS20y7n352zeDnUGVjj+4Tg7Q4G5V6ElMTArSAo8p/ZiZG+2UlOZySTYdryEuN5bTJw6hvsfP5vgpMomvbNm9GpMTglFBa65+fXTO4cTolhdXNjEzzQ8DjoyitbeFvn+7j52/v0PkAmqChBdxFQoyVOj9iwR9esYfNhTVcu2gUJ47PwGoWrCuoIjbK0uOttNFeTU9kDg2O1rfSZneS64cFPjItlvpWOw8u38NzXxTwwY6yARih5ligVwEXQjwjhDgqhNjeafltQojdQogdQogHQzfEgSEpxtpr3eZl20p47JP9XD4/lysW5BJvs7BwdBrQcwghQE5yDKBDCYcKh1wT3v64UK47fjQf/GAJm396BoCuD64JGv5Y4M8BZ3svEEKcAlwIzJRSTgUeCv7QBpakGCt1Pfyw9pTWc9drW5idl8wvLpzqtraXTFD9L+tbev5RZidHIwQc0ZEoQwIjhd4fF0qUxcSEzASSY6OIt1moadICrgkOvQq4lHIV0LmY9XeB30spW13rHA3B2AaUxGhLtwJe29TOjS+sJ85m4fGr52KzeKxtwwJv7aVQlc1iJjNBx4IPNtodTh56f0+vF+DOHK5qwmwSDHfdWflLUoyVmmY9oakJDn31gU8AFgshvhRCrBRCzO9uRSHEjUKI9UKI9eXl5X08XOgxXCjSqM7vwuGU3P7KJoprmnn86jlkJkZ3eH/q8ES/j5GTEqNdKIOMNzcd4a+f7ONPH+4NaLui6mayEqOx9jBx7YvkWCu12gLXBIm+CrgFSAWOA+4BXhXdzOBJKZ+QUs6TUs7LyMjo4+FCT1KMFbtTdqlK+McP9rAyv5yfXzCVuSNTu2xnMZuYmJnAwtFd3+vMiJQY7UIJMu0OJ/e+vpXCqr5dGI0s2lZ7YNUoa5ra3GnygZAca6VG+8A1QaKvAl4E/Ecq1gFOID14wxp4jEpydV630u9tK+Fvn+7nigV5XLVwZLfbLr9jMf++aVGvxxiREkNJTQsOp+x1XY1/7Cmt59/rC7nphQ192t74V5h6ScbpTF2LncSYwIt5JsdEdZnEtDucVOtUe00f6KuAvwmcAiCEmABEARVBGlNYSHIJuPHjqmxo5e7XtjAnL5mfXzClx217y8QzyElWNVfK6nQseLAwLoa7SvvWd9LpcpkFKuD1Le0k2HpOofdFYoy1yyTm75ft5vSHV+oLuyZg/AkjfBlYA0wUQhQJIW4AngHGuEILXwG+KTs7jyOMxGiXgLt+XO9sLaGpzcFvL5neYdKyP4xIMUIJtRslWBi9TKWky/yFPxiiGaB+U99iJ8FHC7XeSI5VpYsNl01dSzsvrztMZWMbB8p16zVNYPgThXKFlDJbSmmVUo6QUj4tpWyTUl4tpZwmpZwjpfx4IAYbSpLcLhQlCG9vKWZSVgKTsvyfpOwNj4Dricxg0eTVy7SgMvDP1RBwc8AWuJ2E6MAt8GTXXMvEHy/H7nDy2voiGl3zLmc8sopXvyoMeJ+aYxedienC24UipWRHcS0njAuuW98IOTvWilpJKflsbznOELgIDAsc4PFP9we8vVHLPRD9djglDa19s8C9m37sLKnj+S8KmJWb7F72wze2BrxPzeBj39EGfvTfbSHvg6sF3EVGgg2bxcTmwmrqmu20tDvJTorufcMAiLaayUiwDXkXynvbSjjq5ed/YtUBrnl6HR/tDn66gBE1tHRaFq9uKGT13sCmYoztA/mhNbju0ny1UOuN1Dib+/nDK/I5XNXEtxePdi9Lj7f52kwTYfzqnZ289OVhVuaHNnRaC7iLGFd1wbc2F7vrgmcFWcBBuVGKaoauC6XV7uB7L23ksn+scS97Ye0hIDCR9JdGV9Pon50/lfHD4rn9lU0BFYsytm9p939sRqRSXyzwpdOyWH7HYtLiovh0TzlZidGcNTWLd28/kXNnZFPR0Bpwez9NeKlubGPN/soOk9DG9+r9HaUhPbYWcC++Pi+X+hY7//yiAICsxOALeE5yzJC2wFvalBAaNdNb2h3u821q63vj6O4wLOi0+Cj+fvVcWtsd3PLSRr/L9hrbG64UfzDKByf2QcBNJsGkrETOnpZFgs3C/edMwmo2MXV4Et+Ylwso14omMnA6Jac9vJIrnlzLXz5SyWAOp2SX63/46R5tgQ8Yx41JIzc1hjc3HwFCY4FnJkZTUT90i/u3dEqI8Z6wNawSf9haVMNv3t3Za2RJY5udKIsJq9nE2Ix4fnvJdDYermHFTv8q/nkscP8F3GOBB+5CMfjNxdPZ+vMzuXBWjnuZ0VikqGroXuCHGsW1zVS5Yvgf+2Qf1Y1t7D1aT2ObgynZiVQ0tLrfDwVawL0wmQSXzc11J3cMSwi+gCfHWGlsc4R8ciNcdBbCQi8xaghAwL/xj7U8+dnBLpmxnWlqdRDnNTG4ZLzK9vU31r4/FnhfXCjedM4fMEJZ6wP4nDThxWgC892Tx2J3Sg5UNLD5cA0AX583AlATmqFCC3gnvjZ3BEKoyaQoS/A/nmRX+rU/BY2qG9v435bioI8hlHgX9aptandX7QNoaPVfJA1/Ym+lVxvb7MRGeYQ0McaKSeB3ZqMRxdIagA+8PggWuC/ibOpC1OBHXXrN4MAQcMNwOFzVxObCGpJjrZw+JROAvUfrQ3Z8LeCdyEmO4fTJmUzIjA/J/pNjOiYM9cRNL27gtpc3dYjoGOx4W+CHq5o4XNVEtNVEcqy1gwvlHyv3c+5fPuvWrWJyfTN7E/CmVodb+ADMJkFybBRVfk4EGnHkvizwsroWnxeC/vjAe8JiNhFjNdPQqmulRAoHyhuJt1mYnZcMwOHKZjYdrmHmiGRykmOIizKztyx0Fnhwv4FDhEevmO1OsQ42KbHKAt9ZUkdeWmyPWZ4bDlUDqvvLsBBMqIYC72iOsroWd+PfpjaH24Xy4tpD/G7ZbkCFHF7mmrzzxkis6a12dmcLHCAl1kp1o38iaFjgvnzgC3/7EenxUaz/sWrE0O5wcvzvPybNdRcVbAscID7aEpCrSRNeDlQ0Mjo9jmirmazEaHaX1pF/tJ6l07MQQjAuM4HdfSzz4A/aAvdBtNXcRRSCRXKs+tF//5XN/ODfm93LfSW7GG6E8k6TntuP1FI8SKsaegthfWs7hS4Bj7cpYXpvWwk/eWs7p00axpj0ON7YWORzP0Ztkp4s8CufXMtneys6WOAAqXFRfk8c+fKB7yiu5faXNwFQ4dWMuKKhlfL6VnaX1mOzmELiYkuItrgtfM3g52BFg3vyOTc1hmXbS5ESd3LW9JxEdhypC0kSG2gBH3AMAQd4b5snRnTj4WqueXodn+xRyS7NXpN3R+s9LpQD5Q2c9+hqbn6xb9X3Qk0HAW+xU1jVxIgUJeCNrXb+8P4epmQn8tcr53Di+HR2HKnrEGny7OcHWb23wp0Z2VOXpC/2VwJgMXX8GqfERlHtrwulrWMcuJSSn7y5nbe95h6MH5/33UAorG+ABJsW8Eih1a5CZA0Bz0uNc7/nEfAk6lvtHOpjuePe0AI+wCTHdqwhbYhDvstPtqdMTXiszPdkLR6ta+X1DUVc/sQaznxkFaBmtsvqWnhw+W6+/fx6Tv7DJ8z8xQd9rosdLLwnMQ9VNtHY5iAvNZY4lwVeUtvM8WPTiIkyMyotjvpWO5Uua9nhlPx+2W6e/fwgZpPLhdLNZK93B53Os/z+WuCFVU20tDsRwnPh+XDXUTa6oggMil2JQd77DLb/28BwoTickvMfXc2LriQozeDh/R2lHKps5HBlE1LCmAwl3F+b6wkJNX7n03KSAFiVX96nYmu9oQV8gPEOeQMocGV9GrPZB8ob2Vlcx92vbWVydiI2i4l1BVXc/doWjta38p0lYzhnehYt7Q4e+2Qff1+5n8NVyg9X29zOlwc7d78bWFo6uSJANf6Nj7ZQUttCS7vTHZ5pWC4FrnM/XNVEq93J3qMN7lDO7lwo+V4TQxUNHV1MKXHKAu/tB2NkyZ07PZuWdgcOp+QP7+9mTHpch5olBRXqougt4Al9SKP3h3ibhYYWO1/sr2DbkdpeU7GHajjqYKWl3cFNL2zgpD986v6tGd/j48em853Fo/nJeZ7y0xMyExiZFsvP3t7R4Y47WGgBH2A6x/7+Z6NKGjpQrkTsi30VfOu5r4i3WXj2uvmMTIvlM1d9j6eunce9Z0/inOnZOCW8vO4w80el8sEPTuKpb84n2mpyZ4CFixYvQdlZrMaSmxpLfJTF7cvPSFD1Pka5vvjGxWuPa7KnsLrJLdzdTWLudd2pXD4/lxduWNjhvdTYKNodstd46uXbS5mcncjEzATsTsnrGwrJL2vgrjMnsvKeU3j+WwvU+FwX2YGwwBOirTS02nlrs3LhGOfpi0OVjUz7+ft8uifiW9JGDN4RJc98fhDwfI8BfnTuFG440VPbxmo28d7ti/n1RdM4ddKwoI9HC3gYuWDmcJ5afYCS2mYOVqgvRnFtC/Ut7Txz3XyykqLd1mpOcoz7Sj8xMwGAdod0t3IzmwQTsxLDLuCtLgs8LS7KXZo3NzWGeC/BG+YS8BEpMZhNwn0XsrtUiZW34dydBb6nrJ4Yq5nfXjydBZ3a2aW4okQqG7q6UWqb2jn/0dWsyi9nw+Fqzp6aRbRVWdt/eD+faTmJLJ2WRUaCjcXj0rGahXvCuIMFHioXis1CdVMby7eXYjEJDlU1dZgP8WbtgUra7E6e+uxgSMai6Yp3RMmB8kbS423uBKzuiLNZuPq4kcREBaevgDdawMPAT8+bwoOXzuCesybidMKv393F4aomt3vlgUtnMMXVLHmCS6y/NifHbb2PTo9jUpZafvxYT8nbKdkJ7CypC4mvzV8MH7hhZafH24iNshBn8xLwRPWe1WxieHK0O1tzjyu6w5vuXSj1jM+Mx2TqWgd2VFosgPui6M1XBVVsO1LLtc+sQ0pYOj3LPbaKhlauO360e58mkyAj3ubO6vSeGO1LNx5/SIi2uEMuL1+Qi5S4J7Y7s6VIuahW76sIabafxsPu0nqirSb393uMl/UdDrSAh4FvnTiar8/LJTc1lutOGMW7W0tod0ie/OY8ln1/MefNGO5e98fnTmbbz8/kzjMnupdZzCbeue1E3r39RBaNTXMvP25MGjVN7SEvoNMTLe0OhMDd8Dc3VdVAT/LyGWfEe2La0+Ntbst2T2k9i8d3bHxd4cOKBuUDNy5unRk3TCVh+UqgcHhd3MakxzF+WDxnTc10LztnelaH9YclRrtdP5UDZIGDukv5zuIxAHzvpY0+m4BsKaxhSnYiVrPQk50DxPYjtYwflkBeqjISRmsBP7a55eRxJMdamTo8kUVj0pic3bEDkMkkfIasWVwV7Lw5Z3o2w5OiedZVTTEctLQ7iLaY3QJnfNFPnugRZu9mwKmxKmKkpd1BQWUjU4Ynkumy0GfmJrO7tK5DGCUoV0Z5favbldSZ5NgoMhJs7PVhlXpnVp41TSVbpMXb2PSTM/j4rpO6xP9nJnpZ4N4+8BBNYhr/6/NnDmdkWhyPXz0H8CR1GbS0O9hTWs8pkzI4d3o2b2woCqhYmCZwjta18FVBFUsmpJPjas4yOkML+DFNUqyVV29axONXz/W7OXJ3WM0mZuelcCSMLdta2p1EW01uITIEfGyGpzSB93kaIX/7XJEnk7IS3HUlzp6ahZTwwY6OlQXzXRN743sodzB+WLxPAfdOsT97qsfaTomLYkxG1/0NS4jmaH0r7Q4nhV6fa6gs8OykaISAS+aokLTTJ2cSYzWzqVNo447iOuxOyYwRyVyzaBT1rXbu+Pdm3d0+hLy9pRinhItnjyDH1R5Ru1A0TMhMINcldP0l2moOqDlBsGm1O7BZzG5XQG6K57w+++EpvHPbiR3WNwTcmMCcmJXAzy+Yyj1nTeTbi0czJj2O5ds7hl8ZAj4xy7cFDsqNcqAHC/zZ6+cz06uVWXdkJtqoaWrn1+/spLCqmVNcdxKhSuQ5aUIGq+45xX13ZTGbmJ6TxObCGvc6VY1tvLzuMKASRubkJTM7L5kVO8t4fGXgbeU0/vHfTUeYMSKJccPiPYbJsNDUTPIXLeBDjGirKaDa1sHGsMCNMDvvC1Nuaqw7scEgNS6KNoeTDYeqibKYGOlK+rnllHFYzSbOmpbFmgOVbuH92Vvb+eMH+SREW3psuJGVFE19q71LE4mqxnZykmM4ZaJ/IV1GFNDzaw5xzXEjuXLhSCB0FrjJJLpczGflJbOzuI5Wu4PmNgdXPrmW1zeoEgSZidEIIXjlxuMYkx7XxdUyVHh7SzFHwlg+Ir+snh3FdVzkqt9+0awcHr96boc7y3CgBXyIEWM1B1TbOti0tDuItppJcmWi5aX1fGdhTHauPVDJ+GHxWMwdv5JLp2XhcEo+3FWGlJLn1xyitrmdiZkJPbqcMly9JSvqPS6F5dtLeWNjESlx/lvPRsTMzBFJ/Pi8yeSlxiKExzU0EMzKTabN4WT7kVpue3kje8rqGTcsnquPy3OvY7OYOXXSMLYdqR1yyT1H61u4/eVNnPD7jwe83dyukjp2ldTx5qYjmE2C82eqAIOYKDNnT8vqZevQo6sRDjFiosy0tDuQUvbbp94XWuxObFYzF80aTkqs1T3Z0x2GgB+saHT7fb2ZnpNETnIMy7eXsnR6tnt5WnxUl3W9McK8yhtayEuLVTVO3toOeCpC+sPckSlcsSCXW08dj81iZmJWApt+ckaXkgihxKirceu/NlFS28KvLprG1Qvzuvx/Z+el8NTqg+wqqfPLPRQpbPby/3+wo4yvz+9avTJULP3zZ4DKw1g8Pt39vRosaAt8iBFtNeOU0OZnT8hg09ruwGYxkRZv45I5I3pd3xBwwB3b7o0QgrOnZfHZ3goOuRJ+AHKSe7aA3QLuCgHcU1bvft5blx9vEqKt/O6SGR0uRAMp3qAmNocl2CipbeHOMyZwzXEjfV6cjZocg7VSZV/ZUlSD2SSIjTKHrVTEkZpmLp7d1cAIN1rAhxhGVmG4JjJb7E73GPwhLc5j0UzKSvS5ztnTsmhzON1+36uPy+Pusyb0uN/OAv7xbk8yjNFwOVIQQnDjkjHcecYEbjt1XLfrGRPHQ62e+JbCWnd00rqCSr+2qW5s44evb+G19YV9Pm6rV3/XuCgzZ04Jv8ukM726UIQQzwDnAUellNM6vXcX8BCQIaWsCM0QNYEQbVXX5JZ2R4fkmYGitd1BdAC3mZlJNqZkJzIpO4ETxqX7XGduXgoZCTZe+lJFXlw2N7fXeu1pcTZMQgn4vqMNPPbxPhaOTmVkWiwXzBx8llRvfNuV1NMTcWES8Kc+O8ALaw9R3diGxWzi/TuWBM3V4HRKthTWcMGs4YwfFs/yHaUcKG/wGfLpzcr8cl5dX8Sr64uYnZfMuGHdRyx1R1mtp0ja0unZIUmF7y/+WODPAWd3XiiEyAXOBA4HeUyafhDjsn67q58RaoxJTH+xWcy89/3FPPz1We4Ssp0xmQRnTc10T8715v8GVRsmNc7GoaomvvfSBmxWM3+6fBYPXjqTE8f7vlBEOkZji4FO6HlrczF2h+TkicOoamxj4+HgRcIcqGikvtXOzNxkzp6WjRC4C32Bqo//9OqD7oJoBt6lBYyCcYFiRL387Pwp/PT8Kb2sHR56FXAp5SrAl+PpEeCHQPgKb2i64Hah2MMj4K12Z5d6JsFg4WhPyQBvt0tPDEuw8dbmYvYebeAvl88mO6nnCdVIx2YxE2U2BdQ8OhgU1zSzZEIGD3xtBibhqULZE5UNrSzfXkq7w8kne47yxX7fN/BG/Pus3GSykqJZNCaN/2wqcnerenD5Hn71zk4ecLXoM9h3tIEx6XGcOmkYf/t0P+c/uprnvyjAHsDckCHgp0wc1mvBqnDRpygUIcSFwBEp5ZbeIh2EEDcCNwLk5eX1uK6m/0SaBe4vM0cku5/7eyt76dwRPPdFAVcflzdkre7OxNnMA2aBO5ySz/dVUNnYxvCkaNWkIz2ux4qY+8sb+O27u1iZX47dKbn37Ek8sFyJ7/dPG096fBQzc5OZ4fp/bymsId5mccdbX3PcSL770kbe31HKOdOz2V+uLO0DrsJlVY1t3PvGVlbsLOOMKZk8dNlMXltfyH83HeFnb+9gd2kdv7tkRq/nVtPUxp8/ygdUTsFgJWABF0LEAv+Hcp/0ipTyCeAJgHnz5mlrPcTY3D7wME1iuhJ5go1RFCsQvnXiaL7lVZv5WMDofDQQPPdFAb96ZycA2a4oncnZiWwtqul2mweW7ebLg1XcsHg0r35V6BZvm8XEnz/aC6gkqY0/OQOr2cTmwhqm5yS53WtnTs1iTHocDyzfzeLx6e5WZYcqmzhQ3sANz693u1NSY6NIirHy7cVj+PbiMfz2vV08seoA9S12rlo4skMhOIC6lna3pf2/rSUUVjVzzvSskBgkwaIvv7SxwGhgixCiABgBbBRCDL4p2mOQGHcUysBb4FJKWuyhscCFEAxLsJFg06kLPRE/gALu7Wcenqys1LHpcRRVN7tdHN602Z18vq+CC2cN5/6lk5nusrLPm5HNnl8vJf/XS/njZTOpb7Gz6XANLe0OdpXUMSsv2b0Ps0nwu0umc7iqie+/spk2u5NpOYm02p2c+seV1DS18ez18zlt0jC+saBjvPgtJ6sInne2lvCzt7d3eO+tzUeY8fMP3GUadhypJTnWymNXzun35xRKAv41SCm3Ae48ZJeIz9NRKIMDw70QjmzMNocTKQmZxbLqh6cQxlLnEUGcq3n0QFDV6InSGO6aX0iLtyGlqp2eHt9xrmJ9QRWNbQ5OdpUxmJ6TyKr8cq5cqFyrURYTp0/JxGwSrMovx2IW2J2yg/sMYOGYNL6zeAxPrDoAwMkThrH9iHLbvP7d4xmbEe+zVEJSrJX7l07id8t2d/l9/HONKsf7+b4KJmQmsKO4jqnDE8OSDBcIvVrgQoiXgTXARCFEkRDihtAPS9NXoi3hs8CNZg6hmMQEdWEYjKFcg4n4IAn49iO1lNa29LiOd7VHw09sRAj56oa00+UbnzcyBYDbTh3PS99e2KEpSVKMldm5yazaW84WrwnMztx5xgR3OeFTJqkCYymx1l5rk9x00ljuPGMChVXN7s+p3eF0302sL6hmb1k9e8rqmdapXPNgpFcLXEp5RS/vjwraaDT9JpwWuHHRsA1in+FQJ95m8dn84Yv9FSTHRLk7PfXErpI6LvnbF6TEWXn95uN9VspstTs4VNnE0mlZLJmQ4b7rMiKEKhtbgY6x14VVTSTYLCTHKj9ztNXsM/b/pAkZPPxhPimxUQxLsPmcRIy2mnn8mrms2FnKnLwUfnzuZM6a6p8X16hiue5gFQvHpPKCq75OUoyVd7eV8O62EgDmjUrtaTeDAu1QHGJ4LPCBn8RsdR0zOkQWuKZ34mxmnz7wK5/8EoCC35/b4/Yt7Q7ueGUziTEWmtscXPvMOl67eRHLtpXQ3O7g+S8Ocd/SSWQlReNwSi6YObxDjZr0Hizww1VN5KbG9uqWWDIhgz+uyGdlfjmn9dAIeHR6HDcuGQv4l+hkMNV1Ebv+ua/cyxaNSeNH507m9Q1FTBmeyJy8FHdnp8GMFvAhRnSUJxNzoDGOOZhn7Yc6ygfe8X/v9JpQ7K3I2QPLd7OnrJ5nr59PYrSFq576kiueWNvBXXLby5uYmJmA1Sy6hGemuhtKt9KZw1VNjPcjI3J6ThLp8TYqGlr9umMIlBEpsbz8neM4VNlIdVM7cTYzF87MISnW2qXc8WBHC/gQI8psQojwxIGH2geu6Z0Em4XGNnsHofbu5Xm4qoncFFUSt7OQr8wv59nPC7ju+FHuScCfnz+V+/6zzb3OjBFJ5KXG8s7WEhaPT+/S2CI5NgqT6HhMUBeRoupmTu3BojYwmQT/d84k7nx1C3Nc/vJgs2hsWpcwwkhEC/gQQwhBjNWsLfBjlDibBSlVxUWjNkpJrac64Y3/3EBxTTOTsxN59eZF7uWVDa3c/doWJmTGc9/SSe7l587Idgv4WVMzufOMiYwfFs+J49J9lqxVJQyiKKhs4tK/f8G0nCSuO34UMVFmWu1Ov+uoXzJnBPNHpTIiZWhnz/YXLeBDkBirmaawCLjLB64FPGwYRaTyy+qZnaes1+IaTzSJ2SQYlR7HV4eqaGy1uwRfct9/tlHb1M7z1y/o8P9LiLYyOy+Z8vpW/nHNPPfyyxd0n1WdFmfjo11lNLU5WH+omufXFLgzKwNpQRasNoNDGX2vOwRJi4+irJcQsFDgscD11ypcnDElk7goM499so+CikaklG4LfMOPT+e97y/mjtPHI6UnrO+VrwpZsbOMH5490afP+dWbFvHRXSf5PYbMpGh3zfUPfrCExeMzegwJ1PQdbYEPQSZlJYalN6LHB64t8HCREG3luhNG8dgn+/lw11FykmOwWU3YLCb3BON010TdtqJa0uKi+OX/dnLiuHS+dYLvsgNWc2AX5AWjUliVX47ZJJiQmcA1x41kVX45QK9lgDWBoU2lIcik7ASO1DRT29w+oMfVFvjg4O4zJ/LhnSfxqwunMj0nicqGNmaMSHJPWg5LjCYjwcaWohru+PdmbFYTf/z6TEzdlPMNlMXjVWKNkU5/oivW+1yvcENNcNCXwyHIZFdnm/yyeuYPYDKCUcJW+8DDixCCccPiGTcsnmsWjcLplHSOHByZGsuybaW0OZw88o2ZZCYGr+KeEYp33fGjAJVctvb+09wJPJrgoQV8CDIpW8Xa7i6pG1gBdyfyaAEfTPiyrDOTomlzudkWjA5uOJ3ZJMj/9VIsXscdzCVZIxkt4EOQrMRokmKs7CqtH9DjGj0EbdqFMujJdlncZpMgMwSd1qN0LsCAoD/lIYgQgklZCezuobB+KDAscJ3IM/gxLOKsxGgsAU5SagYP+j83RJmcncie0voOadQG/91UxO7S4It7a7sDm8U06EtwajwCbtTx1kQmWsCHKBOzEmhsc1BU3dxh+fLtJfzg31t46P09QT9mqNqpaYJPVqIh4DrTMZLRAj5EmeQqmbnLy9I+UtPMD1/fCsDn+yrdPutg0dTm0CGEEUKmFvAhgf61DVEmZCYgBOwuqec37+7kxbWH+MErm3FK+Nn5U2hud7Bmf2VQj7mjuC4iSnBqIDspmjOnZPpVXEozeNFRKEOUOJuFkamxbDtSw4e7jrqXP/KNmSydls2jH+/j2c8L3O2t+ktdSzu7S+u47dTxQdmfJrRYzCaeuHZe7ytqBjXaAh/CTMpKdIv32Iw4XrhhARfPHkG01cwNJ45mZX55jx3EA2HT4RqckgGNO9dojnW0gA9hpuV4ChP95YrZ7hRngGsXjSQx2sKjH+8LyrHWF1RhNokOHcQ1Gk1o0QI+hDl9Sqb7eedmrwnRVq5YkMdHu8qCUjv8q4IqpmQnEm/TXjmNZqDQAj6EMbp2g+/6JLNyk3FK2Fum2mXZHX3ro9lmd7K5sIZ5o0LTPUWj0fhGm0tDGCEEr960qNsO9UZ37l0ldby7rYR/rilg5T2nuJsC+MuO4lpa2p3a/63RDDBawIc4C0Z3L6oj0+KItpr49bs7qWtRncwLq5sCFvD1Baoo0rwQ9S/UaDS+0S6UYxizSTAxM4G6FjsXzRoOQE1TWy9bdeWrgipGpsUyLIglSTUaTe9oC/wY5zcXT6eh1U5WYjRvbi6mujGwJhCPfbKPD3aW8bU5I0I0Qo1G0x1awI9xjOL7tU1KuKsDtMDf2FAEwJULu29yq9FoQkOvLhQhxDNCiKNCiO1ey/4ghNgthNgqhPivECI5pKPUhJyEaAsmATVNgVngVU1tXHPcSOZq/7dGM+D44wN/Dji707IVwDQp5QwgH7g/yOPSDDAmkyA5NiogC9zucFLb3O5ulqvRaAaWXgVcSrkKqOq07AMppd31ci2gHaBDgORYa0AWeE1zO1KiBVyjCRPBiEL5FrCsuzeFEDcKIdYLIdaXl5cH4XCaUJHissBLapv9ys6sblTWeooWcI0mLPRLwIUQPwLswEvdrSOlfEJKOU9KOS8jI6O71TSDgJRYK4cqm1j0u4+5x1U3vCeqXAKepgVcowkLfRZwIcR1wHnAVVLKrn27NBFHcmwUR2pUB5//bSnudX1DwFNitYBrNOGgTwIuhDgb+CFwgZSyKbhD0oSLkamxHV4bYt4dVa4JT+0D12jCgz9hhC8Da4CJQogiIcQNwF+BBGCFEGKzEOLxEI9TMwDccso4Prn7ZN657USEgBv/uZ795Q0+13U6JRtcKfQpcdaBHKZGo3HhTxTKFVLKbCmlVUo5Qkr5tJRynJQyV0o5y/V380AMVhNaTCbB6PQ4puUk8eQ18yiuaea8v6zm1a8K6ewle3PzEf6z6QgANotuZKzRhANdC0Xjk9OnZLLs+0uYlZvMD9/Yyq0vb6K22RNiuKtENUu++8wJ4RqiRnPMowVc0y1ZSdG8+O2F3HPWRJZvL+WCv66muU2FFx6qbGL8sHhu1T0wNZqwoQVc0yNmk+CWU8bx0GUzOFTZxM6SWkAJ+Mi0uDCPTqM5ttECrvGLOXmq1sm+ow1IKTlU1cjItNhettJoNKFEC7jGL0akxBJlMbG/vJHDVU20tDsZpQVcowkrupysxi/MJsGY9Dg+3n2UNzcdIcpsYsHotHAPS6M5ptEWuMZvxg6LZ9/RBhKiLbx5ywnunpoajSY8aAtc4zc3nDiaCcMS+M6S0cRG6a+ORhNu9K9Q4zdz8lLck5kajSb8aBeKRqPRRChawDUajSZC0QKu0Wg0EYoWcI1Go4lQtIBrNBpNhKIFXKPRaCIULeAajUYToWgB12g0mghFDGQ/YiFEOXAowM3SgYoQDGcgiOSxQ+SPH/Q5DBb0OfSPkVLKjM4LB1TA+4IQYr2Ucl64x9EXInnsEPnjB30OgwV9DqFBu1A0Go0mQtECrtFoNBFKJAj4E+EeQD+I5LFD5I8f9DkMFvQ5hIBB7wPXaDQajW8iwQLXaDQajQ+0gGs0Gk2kIqUM6h+QC3wC7AR2AN93LU8FVgB7XY8pruVXAVuBbcAXwEyvfT0DHAW293LMs4E9wD7gPq/lt7qWSSA9wsb+NLDFtf/XgfgIG/9zwEFgs+tvVgR+fz7zGn8x8GYEnsOpwEZgO/A8YBnE5+BzPeAy1xicwDx/xh/Mc+huPwH+HwLSIr/PMVg78hpoNjDH9TwByAemAA8aJwTcBzzgen681we4FPjSa19LgDk9/eMBM7AfGANEoURviuu92cAooMCfD22QjT3Ra72Hvb8METL+54BLI/n702m9N4BrI+kcUHfYhcAE13q/BG4YjOfQ03rAZGAi8CmBCXhQzqG7/QT4ewhIi/w+x2DtqIcP8S3gDNRVKdvrA9njY90U4EinZaN6+fIuAt73en0/cH+ndfr0oQ2SsQvg78C9kTR++ijgg+kcvJYlAtV4XVQj4RyADGC/1/LFwHuD8Rz8WY8ABTzY59B5P338LhUQRAEPqQ9cCDEKdeX5EsiUUpa43ioFMn1scgOwLMDD5KCsDIMi17J+MRjGLoR41nW8ScCjgex4MIwf+I0QYqsQ4hEhhC3AfQ+WcwC4CPhISlkX4L7DfQ4VgEUIYWQPXopyBwTEAJ1DSAnWOXTaT2dCokU9EbKmxkKIeNRt5x1SyjohhPs9KaUUQshO65+C+tBODNWY/GWwjF1Keb0QwowS728Az/qz3SAZ//2oH0cUKn72XtQtvF8MknMwuAJ4KtCNwn0OrmNcDhgX0A8ARyD7CPc5BINgnUPn/YR84H4QEgtcCGFFnehLUsr/uBaXCSGyXe9noyYrjPVnoH4gF0opK3vZd64QYrPr72bgCB2tihGuZUNi7FJKB/AK8LVIGr+UskQqWlEXngX+jH8wnYNr/XTX2N/1d/yD6RyklGuklIullAuAVSj/7WA8h5AQrHPwtZ9Qa5FfBMsX4+XjEcA/gT91Wv4HOk4cPOh6noeanT2+m/2Nomf/nwU4AIzGM3EwtS9+p8Eydtc4xnmN6SHgoUgZv+u9bK8x/Qn4fSR+f4Cbgecj9TcADHM92oCPgFMH4zn4sx6BT2IG5Ry620+g3yXXOgUM5klM1G2HRIXjbHb9nQOkub5Ae4EPgVTX+k+hJoiMddd77etloARoR/mTfM6gu/afj5oB/pHX8ttd29lRYWBPRcLYUXdGn6PCmbYDL+HHBNpgGb9r+cde438RP8IgB9s5uN77FDg7gn8DfwB2oSbu7hjk5+BzPeBi1+tWoAyvicKBOIfu9hNKLfL3T6fSazQaTYSiMzE1Go0mQtECrtFoNBGKFnCNRqOJULSAazQaTYSiBVyj0WgiFC3gGo1GE6FoAddoNJoI5f8BNC5SDaivE8wAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import jqdatasdk as jq\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "jq.auth('13912967392', 'Zcxvbmn1')\n",
    "price_stock_1 = jq.get_price(jq.normalize_code('000066'), start_date='2021-01-01', end_date='2022-01-21', frequency='daily')\n",
    "price_300 = jq.get_price(jq.normalize_code('399300'), start_date='2021-01-01', end_date='2022-01-21', frequency='daily')\n",
    "plt.plot(price_stock_1.index, price_stock_1['close'])\n",
    "plt.plot(price_300.index, price_300['close']/(price_300.loc['2021-01-04']['close']/price_stock_1.loc['2021-01-04']['close']))\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
